A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge

13 September 2022

Papers citing "A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge"

24 / 24 papers shown

Title
In Context Learning and Reasoning for Symbolic Regression with Large Language Models Samiha Sharlin Tyler R. Josephson ReLM LLMAG LRM 77 2 0 22 Oct 2024
SymbolNet: Neural Symbolic Regression with Adaptive Dynamic Pruning for Compression Ho Fung Tsoi Vladimir Loncar S. Dasu Philip C. Harris 181 3 0 18 Jan 2024
Symbolic Regression is NP-hard M. Virgolin S. Pissis 96 64 0 03 Jul 2022
PySINDy: A comprehensive Python package for robust sparse system identification A. Kaptanoglu Brian M. de Silva Urban Fasel Kadierdan Kaheman Andy J. Goldschmidt ... Zachary G. Nicolaou Kathleen P. Champion Jean-Christophe Loiseau J. Nathan Kutz Steven L. Brunton AI4CE 66 149 0 12 Nov 2021
Accelerating Genetic Programming using GPUs Vimarsh Sathia Venkat R. Ganesh Shankara Rao Thejaswi Nanditale 78 8 0 15 Oct 2021
Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication Lukas Kammerer G. Kronberger Bogdan Burlacu Stephan M. Winkler M. Kommenda M. Affenzeller 69 25 0 28 Sep 2021
Contemporary Symbolic Regression Methods and their Relative Performance William La Cava Patryk Orzechowski Bogdan Burlacu Fabrício Olivetti de Francca M. Virgolin Ying Jin M. Kommenda J. Moore 180 259 0 29 Jul 2021
Shape-constrained Symbolic Regression -- Improving Extrapolation with Prior Knowledge G. Kronberger F. O. França Bogdan Burlacu C. Haider M. Kommenda 31 46 0 29 Mar 2021
A Survey of Deep Meta-Learning Mike Huisman Jan N. van Rijn Aske Plaat 175 333 0 07 Oct 2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity S. Udrescu A. Tan Jiahai Feng Orisvaldo Neto Tailin Wu Max Tegmark 65 191 0 18 Jun 2020
Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients Brenden K. Petersen Mikel Landajuela T. Nathan Mundhenk Claudio Santiago Soo K. Kim Joanne T. Kim 52 315 0 10 Dec 2019
AI Feynman: a Physics-Inspired Method for Symbolic Regression S. Udrescu Max Tegmark 158 873 0 27 May 2019
Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks Dongkun Zhang Ling Guo George Karniadakis AI4CE 69 213 0 03 May 2019
Meta-Learning: A Survey Joaquin Vanschoren FedML OOD 63 762 0 08 Oct 2018
Probabilistic Model-Agnostic Meta-Learning Chelsea Finn Kelvin Xu Sergey Levine BDL 264 671 0 07 Jun 2018
Where are we now? A large benchmark study of recent symbolic regression methods Patryk Orzechowski William La Cava J. Moore 41 160 0 25 Apr 2018
Visualizing the Feature Importance for Black Box Models Giuseppe Casalicchio Christoph Molnar B. Bischl FAtt 38 183 0 18 Apr 2018
Synthetic Data Augmentation using GAN for Improved Liver Lesion Classification Maayan Frid-Adar Eyal Klang Michal Amitai Jacob Goldberger H. Greenspan MedIm GAN 62 702 0 08 Jan 2018
On Enhancing Genetic Algorithms Using New Crossovers Ahmad Hassanat Esra’a Alkafaween 24 49 0 08 Jan 2018
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations M. Raissi George Karniadakis AI4CE PINN 67 1,137 0 02 Aug 2017
Elite Bases Regression: A Real-time Algorithm for Symbolic Regression Chen Chen C. Luo Zonglin Jiang 20 24 0 24 Apr 2017
A Probabilistic Linear Genetic Programming with Stochastic Context-Free Grammar for solving Symbolic Regression problems L. F. D. P. Sotto V. V. D. Melo 28 16 0 03 Apr 2017
Monotonic Calibrated Interpolated Look-Up Tables Maya R. Gupta Andrew Cotter Jan Pfeifer Konstantin Voevodski K. Canini Alexander Mangylov Wojtek Moczydlowski A. V. Esbroeck 189 128 0 23 May 2015
The Feature Importance Ranking Measure A. Zien Nicole Krämer Soeren Sonnenburg Gunnar Rätsch FAtt 84 147 0 23 Jun 2009